Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803

The annual EU consumption of energy is approaching 3 Terawatt.hr−1, but the majority of this is powered by fossil fuel. Burning of fossil fuels has produced a global catastrophe, climate change, and carbon-free replacement technologies are urgently required to prevent this from becoming worse in the coming years. The CyanoFactory consortium worked to optimise the organism Synechocystis sp. PCC6803 (herein Synechocystis) to produce industrially relevant levels of bio-hydrogen as one such potential solution. This thesis discusses aspects of this ambitious project, focusing on understanding and optimising the internal protein network of the organism to engineer a functional and efficient system. Synechocystis is a model cyanobacteria – and so has a significant body of research associated with it compared with other cyanobacteria, but is nowhere near as well studied as the other major model organisms such as E. coli or S. cerevisiae – particularly in protein-level studies, although this is changing with time. Whole-proteome studies are highly advanced in medical applications, however bioengineering using proteomics still lags behind studies which directly measure individual proteins, metabolic outputs, or nucleic acid studies. A number of proposals emerge from the literature as the most effective way to move forward, part of which is filling the gaps in the literature for Synechocystis and production strains in general. The major improvement missing from this field is the broad-spectrum inclusion of broadly applicable bioengineering techniques, such as synthetic biology, being integrated with whole-proteome studies, rather than just focusing on individual pathways. This gap is likely to be filled in the near future, with the recent improvements to proteomic technologies and the increasing popularity of the methodology – which has seen a sharp increase since the start of 2015. The current gap between the medical studies and production strains provides an opportunity to test a variety of different approaches, that look more at general whole-cell level responses rather than targeted observations. These gaps in knowledge are assessed herein, and new methods for analysing Synechocystis specifically are proposed. These proposals cover both alterations to the practical protocol, including physically lysing cells based on meta-analysis of the literature with experimental verification, more accurate methods of determining protein levels – which are generally complicated by coloured compounds found in cyanobacteria; and computational protocols for improving the quantity, quality and relevance of the data obtained, including better observation of low-abundance proteins in a complex background, assessment and recommendations for expanding the number of different samples that can be measured simultaneously, and simpler tools for identifying broad-sweeping changes, where metabolic-network derived investigations are unsuitable. Isobaric tags are popular methods for analysing the relative quantity of proteins observed in a cell-wide sample, however there are different technologies for this method. The two most popular tag-based quantification technologies – iTRAQ and TMT – are directly compared, to determine which method is more suitable for analyses in Synechocystis. The study was focused on Synechocystis, however the observations are also more generally applicable to other investigations. To perform this study, a modelled assessment of the ‘proteomic background’ of Synechocystis was carried out, providing an impression of the internal proteome distribution – a valuable set of information for carrying out more accurate engineering of the internal mechanisms with technologies, such as Synthetic Biology. The study found that whilst TMT tags generally produced more quantifications, the iTRAQ tags were more accurate over a greater range – however to take advantage of this would require a larger number of repeated injections of the iTRAQ samples, producing a relatively inflated cost for better quality data. Combining these tools, a direct assessment was carried out of the systemic changes that occur in Synechocystis under hydrogen-producing conditions, along with an assessment of a media proposed for optimised H2 production. This experiment first carried out with the methods used more widely at the start of this analysis, and the second was conducted afterwards, utilising many of the methodological improvements proposed in this thesis. Ultimately, an increase in data quantity and quality was observed. As hydrogen production is a response to a change of conditions, the pathway-level assessment of the proteome changes show a concordant switch between 2 very clear states under the experimental conditions used. This suggests that finding a way to produce hydrogen directly – under normal growth conditions in light – will be extremely challenging as it fundamentally competes with the growth and function of the organism; however an integrated approach, merging the production of high-value side products during the day, coupled with hydrogen production at night for generating power to run the bioreactor system, has a much greater chance of success. A decision on which products should be targeted to make the system economically viable will dictate further analysis of the data. The major conclusions of this work show that the suggested improvements are beneficial to proteomic studies in Synechocystis, producing an improvement to quantity, quality and accessibility of proteomic data. These observations have been applied to hydrogen production systems, demonstrating that whilst bio-hydrogen is unlikely to be the white knight that will save the world from climate change, it can be integrated into large-scale production systems to improve energy efficiency – where the energy saved can reduce costs and power-inputs required from carbon-based fuels. The methods suggested here, whilst ultimately adding little to the assessment of H2 production, have huge potential when integrated into future project focused on the production of more economically viable complex organic molecules or fine chemicals

An energy and resource efficient alkaline flocculation and sedimentation process for harvesting of Chromochloris zofingiensis biomass

Harvesting microalgal cultures is often energetically intensive and costly. To improve efficiencies, a two-step harvesting method utilising alkaline flocculation and sedimentation to pre-concentrate cultures can be used prior to centrifugation. When applied to the microalga Chromochloris zofingiensis, high rates of sedimentation (>90%) were found at low concentrations of base (<10 mM), with the addition of magnesium to the media (via NaOH/MgSO4 or Ca(OH)2/Mg(OH)2) to form Mg(OH)2. The process was scaled to 180 L, where sedimentation was as efficient as that achieved at bench scale. Characterisation of the harvested biomass showed comparable composition (following neutralisation of pH) to biomass recovered solely by centrifugation. The alternative two-step processes were assessed for environmental impacts and cost, which indicated that a two-step harvesting generally performs better than centrifugation alone, but that the locally available electricity source is a critical parameter for optimal solution

Development of Vortex Bioreactor Technology for Decentralised Water Treatment

The vortex bioreactor (VBR) is a simple decentralised water treatment system (DeWaTS) that sits at the interface between swirl flow, biotechnology and chemical engineering. The device utilises swirl flow and suspended activated beads to achieve downstream water processing and has been tested for applications including centrifugal-driven separation, pathogen neutralisation and metal absorption. The VBR was optimised for the treatment of faecally contaminated effluents in the developing world, and the design features related to the key challenges faced by the wastewater industry are highlighted here. The VBR has two aspects that can be modified to generate different reactor conditions: the impeller, where the swirl flow is modified through alterations of rotation speed, and impeller geometry and the suspended activated beads, which facilitate mixing and alter the reactor surface area. Data from testing for some of the different applications mentioned above are presented here, and future planned developments for the technology are discussed

Improving a Synechocystis-based photoautotrophic chassis through systematic genome mapping and validation of neutral sites

[EN] The use of microorganisms as cell factories frequently requires extensive molecular manipulation. Therefore, the identification of genomic neutral sites for the stable integration of ectopic DNA is required to ensure a successful outcome. Herewe describe the genome mapping and validation of five neutral sites in the chromosome of Synechocystis sp. PCC 6803, foreseeing the use of this cyanobacterium as a photoautotrophic chassis. To evaluate the neutrality of these loci, insertion/deletion mutants were produced, and to assess their functionality, a synthetic green fluorescent reporter module was introduced. The constructed integrative vectors include a BioBrick-compatible multiple cloning site insulated by transcription terminators, constituting robust cloning interfaces for synthetic biology approaches. Moreover, Synechocystis mutants (chassis) ready to receive purpose-built synthetic modules/circuits are also available. This work presents a systematic approach to map and validate chromosomal neutral sites in cyanobacteria, and that can be extended to other organisms.This work was supported by the European Commission through the Seventh Framework Programme, FP7-ENERGY-2012-1-2STAGE-308518 (CyanoFactory), from EU FP6-NEST-2005-Path-SYN project BioModularH2 (contract no. 043340) and from National Funds through Fundacao para a Ciencia e a Tecnologia (FCT) (grants SFRH/BD/36378/2007 to F.P., SFRH/BPD/64095/2009 to C.C.P., SFRH/BPD/74894/2010 to P.O.). We also acknowledge the Engineering and Physical Sciences Research Council (EPSRC) for funding (EP/E036252/1) and The University of Sheffield for Scholarship funding. Funding to pay the Open Access publication charges for this article was provided by the European Commission through the Seventh Framework Programme, FP7-ENERGY-2012-1-2STAGE-308518 (CyanoFactory).Pinto, F.; Pacheco, CC.; Oliveira, P.; Montagud, A.; Landels, A.; Couto, N.; Wright, PC.... (2015). Improving a Synechocystis-based photoautotrophic chassis through systematic genome mapping and validation of neutral sites. DNA Research. 22(6):425-437. https://doi.org/10.1093/dnares/dsv024S42543722

Synechocystis Proteomic data (H2 production)

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in <i>Synechocystis sp.</i> PCC6803<i>" </i><a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br><i>Synechocystis</i> <i>sp.</i> PCC6803 was grown in two media conditions, standard BG11 and Burrows media; in two different head-space gas mixtures, air and 100% nitrogen (anaerobic). The experiment was continued until hydrogen gas was detected in the head-space, then the samples were collected by centrifugation and flash-frozen in liquid nitrogen. Proteomic analysis with iTRAQ labels was performed, the data was analysed with the EasyProt software (https://doi.org/10.1016/j.jprot.2012.12.012). <br><br>The first sheet of this dataset contains the full list of all proteins identified in this experiment, and the proceeding pages contain lists of proteins that were differentially regulated with statistical significance under the different environmental conditions (media and headspace). <br

Synechocystis growth rate BG11 vs Burrows media

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803" <a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br>Growth rates were taken from 50 ml culture grown in 250 ml shaking flasks in multiple replicates over a period of 2 weeks. The cells were initially grown in BG11 media, then subbed into BG11 media and Burrows media. <br><br>This data shows that switching to the Burrows media did not significantly impact the rate of growth.<br

Densitometry analysis of Synechocystis proteins

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803" <a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br>Proteins from BG11 and Burrows media were analysed by densitometry, using the software imageJ to calculate values for the different protein lanes - briefly, areas were drawn around regions on the plot and the density of the shading of the pixels was calculated in these regions. The gel image used to generate this data is included in this online data repository. The outputted densitometry values are reported in the csv file. The code in this file is written in R, and uses the package ggplot2; initially the code imports the data, finds the sums the regional densities from each of lanes on the gel, then generates a bar chart from these values.<br

Kalb protein quantification test

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803" <a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br>A protein quantification method, devised by Kalb and Bernlohr, was utilised to remove the influence of phycobilisome pigments on protein quantification prior to analysis. Control samples of bovine serum albumin (BSA) and bovine cytochrome c (cyt) were used as standards of known concentration to investigate this method and how it scaled for individual proteins and mixtures of proteins. <br><br>This dataset shows that there was an over-estimation of cyt that scaled linearly, and a slight underestimation of BSA that did not appear to scale. When combined together, the effects of the linear scaling were still present, however were reduced by half.<br

Proteomic background in Synechocystis

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803" <a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br>The code for the methodology described below was written in Wolfram Mathematica (10.1) and the notebook file is "iTRAQ\_TMT-complexity\_emPAI.nb"<br><br>An in-depth proteomic dataset, comprised of 2 8-plex iTRAQ experiments investigating a mutant against WT \species{Synechocystis} under two different conditions, was generated on a Q-Exactive HF mass spectrometer (data not included in this repository due to size constraints). To calculate the emPAI scores, the ‘observable’ peptide values were calculated as follows. The complete proteome for Synechocystis PCC6803 – Kazusa strain, was downloaded as a fasta file from uniprot (taxonomy:1111708 – accessed August 2015, 3517 protein entries), which is available in this respository.<br><br>This was then merged with the spike-in proteins to make a singular database for analysing the data, by doing this, effects on statistical methods such as false discovery were equal between all analyses. The fasta file was processed in Wolfram Mathematica (version 10.1) to generate an in-silico digest of each of the proteins, excluding any peptides that fell outside a 1000 – 7500 dalton window to replicate the presence of 2+ or 3+ ions observable in the 500 – 2500 m/z window used during the mass spec experimental scan. The emPAI scores for all identified proteins were calculated using the following formula. <br>$$<br> emPAI = 10^{(\frac{N_{observed}}{N_{observable}})} -1<br>$$<br>Where $N_{observed}$ is the number of unique peptides observed for a given protein, and $N_{observable}$ is the total number of unique peptides that could be observed for a given protein.<br><br>This data was then graphed as a histogram to identify the protein concentration distribution and dynamic range. Dynamic range was calculated by taking the exponential of the difference between the maximal and minimal emPAI values.<br

Merging tag-based proteomic experiments

This dataset/code forms part of Andrew Landels' thesis: "Improving proteomic methods and investigating H2 production in Synechocystis sp. PCC6803" <a href="">http://etheses.whiterose.ac.uk/id/eprint/19034</a><br><br>The code in this section is split into two separate scripts, both written in Mathematica. The first (MaxQuant_to_SignifiQunat) converts the data format of files generated by the program MaxQuant and re-orders them into a format that can be input to SignifiQuant - a program in the in-house proteomics pipeline available at the Sheffield University Biological and Chemical Engineering Department. This code reads one or more files within a relevant directory, collects all peptide information, and writes a new file containing all required data. As such, it is both a conversion script and also a data-collecting script.<br><br>The second script investigates methods for merging together two biologically replicated datasets - specifically, one dataset represents a complete experimental replicate of the other. The theory behind this methodology is described in the aforementioned thesis, chapter 4.6. Briefly, this code examines the label intensity distributions, log-transforms the data, then utilises the median correction method to generate a fixed median value (0) and scales the data to generate an equal gradient between the 40th and 60th percentile. <br><br>The protein data in the repeat experiment are then scaled by the protein data in the initial experiment. This slightly disrupts the balancing by median correction, however not significantly. The data are then plotted against each other in a scatter plot, demonstrating systematic improvement of the quality of the between-experiment repeatability. A principal component analysis was then performed, showing a much closer clustering by experimental condition (principal component 1) than of experimental replication deviations (principal component 2), demonstrating success of the method.<br><br>This method shows effective combination of two proteomic datasets that are completely independent experimental repeats, demonstrating for the first time that this methodology is feasible in tag-based proteomic investigations.<br